Methods, devices, and storage media for path planning between underground production facilities

Abstract

This application provides a method, apparatus, and storage medium for path planning between production facilities in underground space, relating to the field of path planning technology. The method employs a traveling salesman model (TSM) determined based on real-time obstacle data and the corresponding building information model (BIM) of the underground space. It updates the target travel time for each passage in real-time based on the obstacle data and BIM. The BIM provides three-dimensional information of the underground space, and integrates physical constraint information into the relevant information of each passage in the directed edge set, providing reliable data for path planning. Furthermore, the real-time obstacle data allows for real-time updates of travel costs, such as target travel time, increasing the real-time nature and feasibility of paths in underground space, improving the accuracy of underground space path planning, and ultimately enhancing transportation efficiency.

Description

Technical Field

[0001] This application relates to the field of path planning technology, specifically to a path planning method, apparatus, and storage medium for underground space production facilities. Background Technology

[0002] Currently, an increasing number of core construction and support facilities (such as concrete production systems, aggregate processing systems, and underground oil depots and storage systems) are shifting from traditional surface deployments to complex underground spaces. However, the underground environment is highly constrained by space and has a complex topological structure, which means that the spatial layout of these facilities is no longer an isolated design problem, but is deeply coupled with the planning of material transportation routes, urgently requiring the search for a globally optimal solution to minimize the cost of cyclical operations.

[0003] However, traditional methods for optimizing material transportation routes face serious challenges: relying on human experience to pre-set fixed routes is difficult to adapt to dynamic task requirements and complex underground topologies (such as one-way passages, height and width restrictions); while static graph search algorithms (such as Dijkstra or A*) can calculate the shortest path between points, they inherently lack the ability to plan the globally optimal access sequence between multiple facility nodes, often resulting in path fragmentation, high repetition rate, and low overall transportation efficiency. Summary of the Invention

[0004] This application provides a method, apparatus, and storage medium for route planning between underground production facilities, which can improve the accuracy of underground route planning and thus improve transportation efficiency.

[0005] This application provides a path planning method between underground space production facilities, including:

[0006] Acquire transportation orders, real-time obstacle data, and building information models corresponding to underground spaces; the real-time obstacle data includes obstacle information for each passage collected by each data acquisition device;

[0007] The node set is determined based on the building information model; the node set includes the coordinates of each production facility;

[0008] A set of directed edges is determined based on building information model and real-time obstacle data; the set of directed edges includes the passage mode, target passage time and physical constraint information of each passage in the building information model;

[0009] The traveling salesman model is determined based on the set of nodes and the set of directed edges;

[0010] The transportation order is semantically parsed to obtain the node access sequence corresponding to the transportation order;

[0011] Based on the node access sequence and the traveling salesman model, the logistics route is determined.

[0012] Optionally, the determination of the directed edge set based on the building information model and real-time obstacle data includes:

[0013] Congestion time is determined based on real-time obstacle data and physical constraint information;

[0014] The basic passage time for each passageway is determined based on building information modeling.

[0015] The target travel time is determined based on the basic travel time and the congestion time.

[0016] Optionally, determining congestion time based on real-time obstacle data and physical constraint information includes:

[0017] If the height of the transport vehicle is greater than or equal to the height limit in the physical constraint information, the congestion time will be determined as the first preset value.

[0018] If the height of the transport vehicle is greater than or equal to the width limit in the physical constraint information, the congestion time will be set as the first preset value.

[0019] If it is determined that there is an obstacle in the passage based on real-time obstacle data, the congestion time is set as the first preset value;

[0020] The number of vehicles in the lane is determined based on real-time obstacle data, and the congestion time is determined based on the number of vehicles.

[0021] Optionally, the step of determining the number of vehicles in the passage based on real-time obstacle data and determining the congestion time based on the number of vehicles includes:

[0022] If the number of vehicles in the channel is greater than the preset number of vehicles, the congestion time is determined based on the preset number of vehicles and the congestion time of a single vehicle; the congestion time of a single vehicle represents the passage delay caused by each additional transport vehicle in the channel.

[0023] Optionally, the determination of the basic passage time for each passage based on the building information model includes:

[0024] For each channel: determine the height difference between the channel end point and the channel start point, and determine the target length of the channel based on the product of the height difference and the preset height difference supplementary length;

[0025] The basic passage time is determined based on the target length of the passage and the preset vehicle speed.

[0026] Optionally, the acquisition of the building information model corresponding to the underground space includes:

[0027] The underground production facilities are set up in layers according to the preset layering rules, and the channels connecting the production facilities are set up.

[0028] Based on the hierarchical setup of production facilities and passageways, a building information model corresponding to the underground space is generated.

[0029] Optionally, the preset hierarchical rules include:

[0030] The living quarters, underground processing plant, underground warehouse, concrete mixing plant, underground oil depot, and explosives warehouse are arranged sequentially from near the surface to far away from the surface.

[0031] To achieve the above and other related objectives, this application provides a path planning device for underground space production facilities, comprising:

[0032] The data acquisition module is used to acquire transportation orders, real-time obstacle data, and building information models corresponding to underground spaces; the real-time obstacle data includes obstacle information for each channel collected by each data acquisition device.

[0033] The first processing module is used to determine a set of nodes based on the building information model; the set of nodes includes the coordinates of each production facility;

[0034] The second processing module is used to determine a set of directed edges based on the building information model and real-time obstacle data; the set of directed edges includes the passage mode, target passage time and physical constraint information of each passage in the building information model;

[0035] The third processing module is used to determine the traveling salesman model based on the set of nodes and the set of directed edges;

[0036] The parsing module is used to perform semantic parsing on the transportation order to obtain the node access sequence corresponding to the transportation order;

[0037] The path determination module is used to determine the logistics path based on the node access sequence and the traveling salesman model.

[0038] Optionally, the second processing module includes:

[0039] The first-time determination unit is used to determine the congestion time based on real-time obstacle data and physical constraint information;

[0040] The second time determination unit is used to determine the basic passage time for each passage based on the building information model;

[0041] The third time determination unit is used to determine the target travel time based on the basic travel time and congestion time.

[0042] To achieve the above and other related objectives, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computer's processor, causes the computer to perform one or more of the aforementioned path planning methods for underground space production facilities.

[0043] As described above, the path planning method, apparatus, and storage medium provided in this application for underground space production facilities have the following beneficial effects:

[0044] This application discloses a path planning method for underground space production facilities. This method employs a traveling salesman model (TSM) determined based on real-time obstacle data and the corresponding building information model (BIM) of the underground space. It updates the target travel time of each passage in real time based on the real-time obstacle data and the BIM. The BIM provides three-dimensional information of the underground space, and physical constraint information is integrated into the relevant information of each passage in the directed edge set, providing reliable data for path planning. Furthermore, the real-time obstacle data can update the target travel time and other travel costs in real time, increasing the real-time nature and feasibility of paths in underground space, improving the accuracy of underground space path planning, and thus improving transportation efficiency.

[0045] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0046] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0047] Figure 1 This is a flowchart illustrating a path planning method between underground space production facilities, as shown in an exemplary embodiment of this application;

[0048] Figure 2 This is a structural block diagram of a path planning device between underground space production facilities, as illustrated in an exemplary embodiment of this application. Detailed Implementation

[0049] The embodiments of this application will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be understood that the preferred embodiments are only for illustrating this application and are not intended to limit the scope of protection of this application.

[0050] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0051] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the present application. However, it will be apparent to those skilled in the art that embodiments of the present application may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the present application.

[0052] Please see Figure 1 , Figure 1 This is a flowchart illustrating a path planning method between underground space production facilities, as shown in an exemplary embodiment of this application. (Reference) Figure 1 It can be seen that the path planning method between production facilities in this underground space may include:

[0053] Step S110: Obtain transportation orders, real-time obstacle data, and building information models corresponding to underground spaces.

[0054] The real-time obstacle data includes obstacle information for each channel collected by each data acquisition device.

[0055] In one embodiment of this application, transport orders, real-time obstacle data, and the building information model corresponding to the underground space can be acquired. The underground space can be divided into multiple production facilities. During production operations, it is necessary to move some materials from one location to another, which can be represented by transport orders. Laser scanning equipment or sensors can be installed in each passage to collect real-time obstacle data. This data indicates whether there are obstacles in the corresponding passage; if obstacles exist, transport vehicles cannot pass. A Building Information Modeling (BIM) is an intelligent model containing geometric, physical, and functional data, and all information is interconnected.

[0056] It should be noted that the path planning method between underground space production facilities provided in this application embodiment can be a terminal, a server, or a server cluster.

[0057] Step S120: Determine the node set based on the building information model.

[0058] The node set includes the coordinates of each production facility.

[0059] In one embodiment of this application, a set of nodes and physical constraint information can be determined based on a Building Information Model (BIM). The BIM includes the IDs of each production facility and their corresponding coordinates, and the coordinates and IDs of each production facility can be combined to obtain the set of nodes.

[0060] Step S130: Determine the set of directed edges based on the building information model and real-time obstacle data.

[0061] The directed edge set includes the traffic pattern, target travel time, and physical constraint information for each passage in the building information model. The directed edge set may also include the target length of each passage.

[0062] In one embodiment of this application, the passage mode can characterize whether the passage allows one-way or two-way passage; the target passage time can characterize the time it takes for transport vehicles to pass through the passage; physical constraint information can include the height limit, width limit, and service capacity of each passage, where service capacity characterizes how many transport vehicles can pass through the passage per hour. The set of directed edges can be determined based on the Building Information Model (BIM), real-time obstacle data, and physical constraint information. The physical constraint information extracted from the BIM, the passages connecting the various production facilities, the length of each passage, and the physical constraint information can determine the basic information of the directed edges.

[0063] Step S140: Determine the traveling salesman model based on the set of nodes and the set of directed edges.

[0064] In one embodiment of this application, the Traveling Salesman Problem (TSP) can be determined based on a set of nodes and a set of directed edges. The Traveling Salesman Problem (TSP) is the most basic routing problem, which seeks the minimum path cost for a single traveler starting from a starting point, passing through all given demand points, and finally returning to the origin. The TSP can include each node, the channels connecting the nodes, and the target travel time for each channel.

[0065] The core of the TSP method lies in finding the optimal order of single-loop access for a set of fixed facility nodes. Compared with traditional point-to-point path search, TSP applied to path planning in underground space can directly optimize the total distance / time of the overall loop, fundamentally avoiding redundancy and conflicts caused by path segment splicing. At the same time, its model framework has good scalability, making it easy to incorporate various physical constraints (such as passage restrictions and time windows) and operational requirements of underground space, providing a strong theoretical tool foundation for the planning of efficient and intensive underground material transportation systems.

[0066] Step S150: Perform semantic parsing on the transportation order to obtain the node access sequence corresponding to the transportation order.

[0067] In one embodiment of this application, semantic parsing can be performed on a transportation order to obtain the node access sequence corresponding to the transportation order. The origin, destination, and waypoints in the transportation order can be obtained through semantic parsing, which is the node access sequence. The node access sequence may also include other restrictive information such as time limits for each node.

[0068] Step S160: Determine the logistics route based on the node access sequence and the traveling salesman model.

[0069] In one embodiment of this application, a logistics path can be determined based on a node access sequence and a traveling salesman model. The logistics path can be the route through which transport vehicles travel to each node in the node access sequence. The path with the minimum sum of travel times can be determined as the logistics path; alternatively, the path with the minimum sum of target lengths for each route can also be determined as the logistics path, which can be specifically set by the operator.

[0070] In one possible implementation, step S130, which involves determining the set of directed edges based on the building information model and real-time obstacle data, may include steps S131 to S133.

[0071] Step S131: Determine the congestion time based on real-time obstacle data and physical constraint information.

[0072] In one embodiment of this application, congestion time can be determined based on real-time obstacle data and physical constraint information in the building information model.

[0073] In one possible implementation, step S131, which determines the congestion time based on real-time obstacle data and physical constraint information, may include: if the height of the transport vehicle is greater than or equal to the height limit in the physical constraint information, then the congestion time is determined as a first preset value; if the height of the transport vehicle is greater than or equal to the width limit in the physical constraint information, then the congestion time is determined as a first preset value; if it is determined based on real-time obstacle data that there are obstacles in the passage, then the congestion time is determined as a first preset value; the number of vehicles in the passage is determined based on real-time obstacle data, and the congestion time is determined based on the number of vehicles.

[0074] For example, the first preset value can be infinity. When the height or width of the transport vehicle does not meet the height or width limit corresponding to the passage, the transport vehicle cannot pass through the passage. The congestion time can be set to infinity to indicate that the passage is unavailable in the route planning.

[0075] The process of determining the number of vehicles in the channel based on real-time obstacle data and determining the congestion time based on the number of vehicles may include: if the number of vehicles in the channel is greater than the preset number of vehicles, then the congestion time is determined based on the preset number of vehicles and the congestion time of a single vehicle; the congestion time of a single vehicle represents the passage delay caused by each additional transport vehicle in the channel.

[0076] It should be noted that LiDAR point cloud clustering can be used to identify moving objects whose dimensions match those of transport vehicles, thus determining the number of vehicles in the passage; the number of transport vehicles in the passage is equivalent to the total number of vehicles in the passage. Alternatively, real-time images of the passage can be captured by cameras, and a pre-trained YOLO model can be used to detect vehicle bounding boxes in real time, determining the number of vehicle bounding boxes as the total number of vehicles in the passage.

[0077] The congestion time per vehicle can be determined through calibration. For example, historical data can be used to extract travel time records for lanes with 3 or more vehicles to obtain the average travel time T_avg_congested under congested conditions; and historical data can be used to extract travel time records for lanes with 1 vehicle to obtain the average travel time T_avg_free under uncongested conditions. The average number of vehicles in the corresponding lane during congestion is N_avg. Therefore, the congestion time per vehicle t_unit = (T_avg_congested - T_avg_free) / N_avg. If no historical data is available, the congestion time per vehicle can be set to a preset value of 10 seconds per vehicle.

[0078] For example, when the traffic is smooth, T_avg_free = 20 seconds. When the traffic is congested, the average number of vehicles N_avg is 5, and T_avg_congested = 65 seconds. Then the congestion time per vehicle t_unit = (65-20) / 5 = 9 seconds / vehicle. This means that for each additional transport vehicle, the travel time increases by 9 seconds.

[0079] In another possible implementation, real-time acquisition of rock mass microseismic monitoring data and gas sensor monitoring data corresponding to the channel can be used. When the rock mass microseismic monitoring data is greater than 0.2g or the methane concentration in the gas sensor monitoring data is greater than or equal to 5% LEL, the congestion time corresponding to the channel can be set to infinity. LEL can characterize the lower explosive limit of methane.

[0080] Step S132: Determine the basic passage time for each passage based on the building information model.

[0081] In one embodiment of this application, the basic passage time for each passage can be determined based on a building information model (BIM). The length of each passage can be extracted based on the BIM, and the basic passage time can be the time it takes for a transport vehicle to pass through the passage at a preset speed under ideal conditions where the passage is uncongested and unobstructed.

[0082] For example, if a transport vehicle can pass through a channel of length L at a preset speed v, then the basic travel time t1 = L / v.

[0083] In one possible implementation, the process of determining the basic passage time for each passage based on the building information model may include: for each passage: if the height difference between the end point and the beginning point of the passage is determined, the target length of the passage is determined based on the product of the height difference and a preset height difference supplementary length; the basic passage time is determined based on the target length of the passage and a preset vehicle speed.

[0084] Traditional logistics transportation selects the shortest path between two points in a plane. After reading the location coordinates (including 3D coordinates) of each production facility from the Building Information Model (BIM), ramps and shafts are converted into equivalent transportation costs: each meter of elevation gain is weighted at 10 meters of horizontal distance. For example, a 5° ramp with a 10-meter elevation gain has a target channel length = plane distance + 100 meters. That is, if the elevation gain is less than 1 meter, the horizontal distance of the channel can be determined as the target channel length. When the elevation gain meets the aforementioned conditions, the target length can be obtained by equivalently replacing the elevation gain with the increase in channel length.

[0085] Step S133: Determine the target travel time based on the basic travel time and congestion time.

[0086] In one embodiment of this application, the target travel time can be determined based on the basic travel time and congestion time. For example, the sum of the basic travel time and congestion time can be used to determine the target travel time.

[0087] Optionally, the process of obtaining the building information model corresponding to the underground space may include: setting up the underground production facilities in layers according to preset layering rules and setting up the passages connecting the production facilities; and generating the building information model corresponding to the underground space based on the layered production facilities and passages.

[0088] The pre-defined stratification rules include: arranging living quarters, underground processing plants, underground warehouses, concrete mixing plants, underground oil depots, and explosives warehouses sequentially from near the surface to far away from the surface.

[0089] Specifically, the process of setting up production facilities in layers can include:

[0090] Step 1: Layered design of underground space - Vertically partition different underground facilities according to "safety level".

[0091] Due to the complex structure and limited space of underground production facilities, their layered layout prioritizes safety and logistical efficiency. Underground production facilities primarily include several core structures such as living quarters, underground processing plants, underground warehouses, concrete mixing plants, and underground oil and explosives depots. Therefore, layering these structures allows for full utilization of underground space and ensures the adaptability and orderliness of underground logistics flow. The specific layering logic is as follows:

[0092] The living quarters are located near the surface, such as 5m underground, to ensure timely evacuation in the event of major geological risks. The living quarters are connected to the surface through vertical shafts to ensure that personnel can be evacuated within 30 seconds.

[0093] The underground processing plant and underground warehouse are located in the middle underground level, such as -15m underground, to balance the input of raw materials and the output of finished products. The dust generated is discharged upward to the ground through a dedicated vertical shaft.

[0094] Concrete mixing plants are located in deeper underground layers, such as -25m underground. This layer is close to the underground processing plant and aggregate source, and can be directly connected by belt conveyors to reduce material transfer time.

[0095] The underground oil depot and explosives depot are located in underground strata, such as at -35m underground. This level is far away from the living quarters, so that casualties can be minimized in the event of a venting explosion. At the same time, it is close to the concrete mixing plant, which reduces energy transfer time and improves logistics efficiency.

[0096] Based on geological conditions, high-risk facilities are forcibly bound to deep, stable layers, while living quarters dynamically adapt to the location of surface escape exits. The concrete system is intelligently anchored based on the elevation of aggregate sources, forming vertical functional zones that coexist with the geological structure. This system ensures an adaptive and safe layout of underground space under complex geological conditions, significantly improving space utilization compared to traditional methods.

[0097] Step 2: Nesting of underground facilities

[0098] Due to the intricate and complex nature of underground production facilities, their large footprint, and the limited availability of underground space, it is essential to make the most of this space. After determining the layered locations of the core structures described in Step 1—including the living quarters, underground processing plant, underground warehouse, concrete mixing plant, underground oil depot, and explosives depot—other necessary facilities can be nested parallel to each core facility on each floor. Specifically:

[0099] The steel bar plant and the waste recycling station are nested together, sharing a rubber vibration isolation foundation. A double-layer microporous aluminum plate sound-absorbing wall is set in the middle. The vibration energy of the waste crusher is absorbed and converted by the foundation, which simultaneously reduces the vibration amplitude of the steel bar processing equipment. The sound-absorbing wall is embedded with a metal recycling conveyor, which allows the waste steel slag to be directly transported to the crushing area of ​​the recycling station.

[0100] The explosion-proof wall of the oil depot is nested with a sewage treatment tank, extending the 1.5-meter-thick explosion-proof wall to 2.2 meters, and embedding a stainless steel sewage treatment tank (50m³) within the interlayer. 3 The pre-embedded pH sensor and dosing pipeline in the wall not only meet the requirements for hazardous chemical isolation but also utilize the wall space to complete wastewater neutralization treatment (pH adjustment range 6.5-8.5), saving 300m² compared to separate construction. 2 space.

[0101] A sewage treatment system is embedded in the explosion-proof wall interlayer to complete the neutralization treatment of hazardous waste using the wall space; a vibration-noise coordinated control base is developed simultaneously: the steel plant and the waste station share a rubber vibration isolation foundation, with a microporous aluminum plate sound-absorbing wall in the middle (noise reduction of 30dB), forming a "space folding" effect, which significantly reduces energy consumption compared to conventional layouts.

[0102] Step 3: Establish an underground infrastructure network

[0103] After determining the layered locations of the underground production facilities according to the method described in step 1, an underground logistics channel network is established to ensure that all underground facilities are interconnected and form a functional whole. The specific steps are as follows:

[0104] (1) Construct an 8m wide two-way main road, which serves as the "main artery" of the underground logistics system. The road ascends vertically from the -35m oil depot level to the surface, connecting various functional areas with two lanes of 8m net width. Its layout adopts a spiral gentle slope design (slope ≤ 8%). This passage mainly handles the transportation of conventional materials such as sand, gravel, and equipment, and achieves efficient passage through time-based control (such as prohibiting dangerous goods during the day).

[0105] (2) A vertical shaft logistics tower is built, with a 5m diameter circular vertical shaft running through each floor. A double-rail elevator is embedded in the shaft wall. This channel can utilize the potential energy of the height difference to allow sand and gravel to reach the -25m mixing station directly through the wear-resistant ceramic chute, which reduces energy consumption by 40% compared to belt conveyor. At the same time, the intelligent booster system dynamically supplies oxygen to the -5m living area to maintain the oxygen concentration in the underground space.

[0106] (3) For dangerous goods, such as fuel, a separate independent dangerous goods loop is established. The independent dangerous goods loop is designed specifically for high-risk materials such as fuel and explosives, and constructs a fully enclosed explosion-proof transportation network. The loop adopts a double-layer structure: the lower layer is a 4m wide explosion-proof road surface (paved with basalt aggregate concrete, with a static dissipation rate of ≥95%), and the upper layer is equipped with ventilation and explosion-proof pipes; it is physically isolated from the main road through grade-separated overpasses or underpasses to avoid the risk of intersection. The loop implements time-sharing control (dedicated passage from 22:00 to 6:00) and is equipped with an intelligent monitoring system (real-time early warning from methane / vibration sensors). Its advantage lies in completely isolating dangerous goods from the regular logistics flow, guiding the accident shock wave to the uninhabited area through directional explosion-proof design (vertical shaft inclination angle of 45°), and improving transportation efficiency by 35% during dedicated time periods, thus ensuring overall operational safety.

[0107] It should be noted that the dispatching system implements dual control in time and space: time-limited exclusive passage - gravel trucks are restricted to using the main road from 0:00 to 6:00 in the morning, and dangerous goods vehicles exclusively occupy the explosion-proof ring road from 10:00 to 16:00 in the daytime; when the GPS positioning of two vehicles is about to enter the 200-meter intersection area, the system automatically instructs the lower priority vehicle to drive into the side wall avoidance compartment (3m×8m expansion space), and releases it after the higher priority vehicle has passed.

[0108] Traditional route planning problems primarily target surface-level infrastructure. Shifting traditional infrastructure from "surface" to "underground" presents the following core challenges:

[0109] (1) The spatial structure of underground production facilities is complex. Large-scale underground storage and production sites for construction materials such as sand, gravel, cement, steel, and fuel are arranged within the rock mass. Concrete production system sites, material conveying channels such as vehicles, belt conveyors, and vertical shafts all exist in the form of underground spatial structures. These underground spatial structures are interconnected and mutually influential, constrained by geological conditions and production and transportation processes, and their shapes vary. This brings great difficulty to the design and construction of the shape structure of each space.

[0110] (2) Complex underground logistics circulation. Due to the massive scale of the project, the underground space spanned by the cascade hydropower stations is extensive and the spatial layout is complex. The required quantities of production materials such as cement, steel, oil, explosives, and sand and gravel, as well as the storage and transportation of excavated stone slag from the chambers, are enormous. The production process is complex, and the connection between transportation channels, storage sites, and the main underground construction work faces are intertwined. The adaptability, orderliness, and economy of underground logistics circulation face challenges, which is a key problem affecting the success or failure of the construction of giant hydropower stations. Multi-layered caverns (such as the -10-meter living area and the -30-meter oil depot) have passages that intersect like overpasses. Traditional surface TSPs only need to consider the horizontal distance, while underground facilities, although the straight-line distance between two points is short, may require detours of several kilometers to connect.

[0111] (3) Setting up a super-large underground site is difficult and subject to many constraints. Not only are there geological risks, but also a variety of factors such as safety and environment need to be considered. For example, the rock strata in some areas may collapse, so the site selection of facilities should avoid geologically weak zones as much as possible. If an accident occurs in facilities such as oil depots or gunpowder depots, the shock wave will be amplified several times in the enclosed space, so absolute isolation needs to be ensured.

[0112] To address the aforementioned problems, the path planning method for underground space production facilities provided in this application can achieve the following objectives:

[0113] (1) Achieving efficient collaborative layout in three-dimensional space. In response to the problem of complex and mutually restrictive structure of underground cavern groups, this invention establishes a dynamic coupling model between underground facilities and rock mass structure, and transforms geological conditions (such as the coordinates of the stable rock mass zone), production process (such as the aggregate processing-concrete mixing link), and transportation requirements into spatial layout constraint parameters. This enables a three-dimensional layered layout of the oil depot deep buried stable layer, the mixing plant close to the aggregate source, and the living area near the ground surface, so that each functional unit can mesh like precision gears in the limited underground space, reducing rework caused by structural conflicts.

[0114] (2) Breaking the bottleneck of dynamic optimization of three-dimensional logistics network. In order to solve the problem of "false proximity" caused by multi-layer caverns (such as a straight distance of 100 meters from -10m to -30m but requiring a detour of 3 kilometers), this invention develops a three-dimensional TSP path engine: converting elevation difference into equivalent transportation cost (1 meter uphill = 10 meters horizontal), establishing a time-space diversion strategy (dedicated nighttime channel for dangerous goods), and constructing a transportation scheme that takes into account both the shortest path and safety and disaster avoidance, so as to greatly improve the efficiency of underground logistics and completely reverse the dilemma of "seeing but taking a long detour".

[0115] Constructing a full life-cycle isolation system for hazardous sources. Addressing the risk of amplified shockwaves from oil depot and explosives depot accidents in enclosed underground spaces, this invention establishes safety protection measures: Physically, absolute isolation is achieved through the construction of explosion-proof shafts; digitally, the TSP algorithm dynamically marks hazardous areas (weight coefficient ∞) and plans zero-intersection paths; operationally, time-slot transportation (tanker trucks only allowed to travel between 22:00 and 6:00) and an emergency avoidance mechanism are implemented, forming a triple protection system from spatial layout to transportation scheduling, aiming to significantly reduce accident risks.

[0116] Figure 2 This is a block diagram illustrating a path planning device between underground space production facilities, as shown in an exemplary embodiment of this application. Figure 2 As shown, the exemplary underground space production facility path planning device 200 includes:

[0117] The data acquisition module 210 is used to acquire transportation orders, real-time obstacle data, and building information models corresponding to underground spaces; the real-time obstacle data includes obstacle information of each channel collected by each data acquisition device;

[0118] The first processing module 220 is used to determine the node set based on the building information model; the node set includes the coordinates of each production facility;

[0119] The second processing module 230 is used to determine a set of directed edges based on the building information model and real-time obstacle data; the set of directed edges includes the passage mode, target passage time and physical constraint information of each passage in the building information model;

[0120] The third processing module 240 is used to determine the traveling salesman model based on the set of nodes and the set of directed edges;

[0121] The parsing module 250 is used to perform semantic parsing on the transportation order to obtain the node access sequence corresponding to the transportation order;

[0122] The route determination module 260 is used to determine the logistics route based on the node access sequence and the traveling salesman model.

[0123] In one embodiment of this application, the second processing module includes:

[0124] The first-time determination unit is used to determine the congestion time based on real-time obstacle data and physical constraint information;

[0125] The second time determination unit is used to determine the basic passage time for each passage based on the building information model;

[0126] The third time determination unit is used to determine the target travel time based on the basic travel time and congestion time.

[0127] In one embodiment of this application, the first-time determination unit is further configured to:

[0128] If the height of the transport vehicle is greater than or equal to the height limit in the physical constraint information, the congestion time will be determined as the first preset value.

[0129] If the height of the transport vehicle is greater than or equal to the width limit in the physical constraint information, the congestion time will be set as the first preset value.

[0130] If it is determined that there is an obstacle in the passage based on real-time obstacle data, the congestion time is set as the first preset value;

[0131] The number of vehicles in the lane is determined based on real-time obstacle data, and the congestion time is determined based on the number of vehicles.

[0132] In one embodiment of this application, the first-time determination unit is further configured to:

[0133] If the number of vehicles in the channel is greater than the preset number of vehicles, the congestion time is determined based on the preset number of vehicles and the congestion time of a single vehicle; the congestion time of a single vehicle represents the passage delay caused by each additional transport vehicle in the channel.

[0134] In one embodiment of this application, the second time determination unit is further configured to:

[0135] For each channel: determine the height difference between the channel end point and the channel start point, and determine the target length of the channel based on the product of the height difference and the preset height difference supplementary length;

[0136] The basic passage time is determined based on the target length of the passage and the preset vehicle speed.

[0137] In one embodiment of this application, the data acquisition module includes:

[0138] The hierarchical division unit is used to set up underground production facilities in layers according to preset hierarchical rules and to set up channels connecting each production facility;

[0139] The model generation unit is used to generate building information models of the underground space based on the hierarchical settings of each production facility and passage.

[0140] In one embodiment of this application, the preset layering rules include:

[0141] The living quarters, underground processing plant, underground warehouse, concrete mixing plant, underground oil depot, and explosives warehouse are arranged sequentially from near the surface to far away from the surface.

[0142] It should be noted that the underground space production facility path planning device and the underground space production facility path planning method provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the underground space production facility path planning device provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0143] Embodiments of this application also provide an electronic device, including: one or more processors; and a storage device for storing one or more programs, which, when executed by one or more processors, enable the electronic device to implement the path planning method for underground space production facilities provided in the above embodiments.

[0144] Another aspect of this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a computer's processor, causes the computer to perform the path planning method for underground space production facilities provided in the various embodiments described above. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not incorporated into the electronic device.

[0145] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the path planning method for underground space production facilities provided in the various embodiments described above.

[0146] In the embodiments of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The terms "comprising" and "including" as used throughout the specification and claims are open-ended terms and should therefore be interpreted as "comprising but not limited to".

[0147] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A path planning method between underground production facilities, characterized in that, include: Acquire transportation orders, real-time obstacle data, and building information models corresponding to underground spaces; The real-time obstacle data includes obstacle information for each channel collected by each data acquisition device; The node set is determined based on the building information model; the node set includes the coordinates of each production facility; A set of directed edges is determined based on building information model and real-time obstacle data; the set of directed edges includes the passage mode, target passage time and physical constraint information of each passage in the building information model; The traveling salesman model is determined based on the set of nodes and the set of directed edges; The transportation order is semantically parsed to obtain the node access sequence corresponding to the transportation order; Based on the node access sequence and the traveling salesman model, the logistics route is determined; The method for determining the set of directed edges based on building information modeling and real-time obstacle data includes: Congestion time is determined based on real-time obstacle data and physical constraint information; The basic passage time for each passageway is determined based on building information modeling. Target travel time is determined based on basic travel time and congestion time. The method of determining congestion time based on real-time obstacle data and physical constraint information includes: If the height of the transport vehicle is greater than or equal to the height limit in the physical constraint information, the congestion time will be set to the first preset value; the first preset value is infinity. If the width of the transport vehicle is greater than or equal to the width limit in the physical constraint information, the congestion time will be determined as the first preset value. If it is determined that there is an obstacle in the passage based on real-time obstacle data, the congestion time is set as the first preset value; The number of vehicles in the lane is determined based on real-time obstacle data, and the congestion time is determined based on the number of vehicles. The method of determining the basic passage time for each passage based on building information modeling includes: For each channel: determine the height difference between the channel end point and the channel start point, and determine the target length of the channel based on the product of the height difference and the preset height difference supplementary length; The basic passage time is determined based on the target length of the passage and the preset vehicle speed.

2. The path planning method between underground space production facilities according to claim 1, characterized in that, The method of determining the number of vehicles in the passage based on real-time obstacle data and determining the congestion time based on the number of vehicles includes: If the number of vehicles in the channel is greater than the preset number of vehicles, the congestion time is determined based on the preset number of vehicles and the congestion time of a single vehicle; the congestion time of a single vehicle represents the passage delay caused by each additional transport vehicle in the channel.

3. The path planning method between underground space production facilities according to claim 1, characterized in that, The acquisition of the building information model corresponding to the underground space includes: The underground production facilities are set up in layers according to the preset layering rules, and the channels connecting the production facilities are set up. Based on the hierarchical setup of production facilities and passageways, a building information model corresponding to the underground space is generated.

4. The path planning method between underground space production facilities according to claim 3, characterized in that, The preset hierarchical rules include: The living quarters, underground processing plant, underground warehouse, concrete mixing plant, underground oil depot, and explosives warehouse are arranged sequentially from near the surface to far away from the surface.

5. A path planning device between underground production facilities, characterized in that, include: The data acquisition module is used to acquire transportation orders, real-time obstacle data, and building information models corresponding to underground spaces; The real-time obstacle data includes obstacle information for each channel collected by each data acquisition device; The first processing module is used to determine a set of nodes based on the building information model; the set of nodes includes the coordinates of each production facility; The second processing module is used to determine a set of directed edges based on the building information model and real-time obstacle data; the set of directed edges includes the passage mode, target passage time and physical constraint information of each passage in the building information model; The third processing module is used to determine the traveling salesman model based on the set of nodes and the set of directed edges; The parsing module is used to perform semantic parsing on the transportation order to obtain the node access sequence corresponding to the transportation order; The path determination module is used to determine the logistics path based on the node access sequence and the traveling salesman model; The second processing module includes: The first-time determination unit is used to determine the congestion time based on real-time obstacle data and physical constraint information; The second time determination unit is used to determine the basic passage time for each passage based on the building information model; The third time determination unit is used to determine the target travel time based on the basic travel time and congestion time. The method of determining congestion time based on real-time obstacle data and physical constraint information includes: If the height of the transport vehicle is greater than or equal to the height limit in the physical constraint information, the congestion time will be set to the first preset value; the first preset value is infinity. If the width of the transport vehicle is greater than or equal to the width limit in the physical constraint information, the congestion time will be determined as the first preset value. If it is determined that there is an obstacle in the passage based on real-time obstacle data, the congestion time is set as the first preset value; The number of vehicles in the lane is determined based on real-time obstacle data, and the congestion time is determined based on the number of vehicles. The method of determining the basic passage time for each passage based on building information modeling includes: For each channel: determine the height difference between the channel end point and the channel start point, and determine the target length of the channel based on the product of the height difference and the preset height difference supplementary length; The basic passage time is determined based on the target length of the passage and the preset vehicle speed.

6. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by the computer's processor, causes the computer to perform the path planning method between underground space production facilities as described in any one of claims 1 to 4.

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